epoch 0: {'accuracy': 0.8553908109097565} , current_best_acc: 0.8553908109097565 train_loss: 0.43196678161621094
epoch 1: {'accuracy': 0.8865092440051254} , current_best_acc: 0.8865092440051254 train_loss: 0.3508402705192566
epoch 2: {'accuracy': 0.8828482518762585} , current_best_acc: 0.8865092440051254 train_loss: 1.00995934009552
epoch 3: {'accuracy': 0.8989566172432729} , current_best_acc: 0.8989566172432729 train_loss: 0.33873850107192993
epoch 4: {'accuracy': 0.8976752699981695} , current_best_acc: 0.8989566172432729 train_loss: 0.5210118889808655
epoch 5: {'accuracy': 0.899505766062603} , current_best_acc: 0.899505766062603 train_loss: 0.056467972695827484
epoch 6: {'accuracy': 0.9084751967783269} , current_best_acc: 0.9084751967783269 train_loss: 0.6042883992195129
epoch 7: {'accuracy': 0.8954786747208493} , current_best_acc: 0.9084751967783269 train_loss: 0.13294631242752075
epoch 8: {'accuracy': 0.90481420464946} , current_best_acc: 0.9084751967783269 train_loss: 0.22524729371070862
epoch 9: {'accuracy': 0.9057294526816767} , current_best_acc: 0.9084751967783269 train_loss: 0.6333118081092834
epoch 10: {'accuracy': 0.8940142778693025} , current_best_acc: 0.9084751967783269 train_loss: 0.20362646877765656
epoch 11: {'accuracy': 0.9009701629141498} , current_best_acc: 0.9084751967783269 train_loss: 0.17509090900421143
epoch 12: {'accuracy': 0.9062786015010068} , current_best_acc: 0.9084751967783269 train_loss: 0.3611968457698822
epoch 13: {'accuracy': 0.909573494416987} , current_best_acc: 0.909573494416987 train_loss: 0.07481373101472855
epoch 14: {'accuracy': 0.90426505583013} , current_best_acc: 0.909573494416987 train_loss: 0.12312797456979752
epoch 15: {'accuracy': 0.9022515101592532} , current_best_acc: 0.909573494416987 train_loss: 0.09327603131532669
epoch 16: {'accuracy': 0.9092073952041003} , current_best_acc: 0.909573494416987 train_loss: 0.28653383255004883
epoch 17: {'accuracy': 0.9125022881200805} , current_best_acc: 0.9125022881200805 train_loss: 0.13861346244812012
epoch 18: {'accuracy': 0.9141497345780707} , current_best_acc: 0.9141497345780707 train_loss: 0.2599187195301056
epoch 19: {'accuracy': 0.9106717920556471} , current_best_acc: 0.9141497345780707 train_loss: 0.08905483782291412
epoch 20: {'accuracy': 0.9108548416620904} , current_best_acc: 0.9141497345780707 train_loss: 1.0111416578292847
epoch 21: {'accuracy': 0.9139666849716274} , current_best_acc: 0.9141497345780707 train_loss: 0.36082974076271057
epoch 22: {'accuracy': 0.9152480322167308} , current_best_acc: 0.9152480322167308 train_loss: 0.1781819611787796
epoch 23: {'accuracy': 0.9141497345780707} , current_best_acc: 0.9152480322167308 train_loss: 0.11893875896930695
epoch 24: {'accuracy': 0.9068277503203368} , current_best_acc: 0.9152480322167308 train_loss: 0.3459784984588623
epoch 25: {'accuracy': 0.9136005857587406} , current_best_acc: 0.9152480322167308 train_loss: 0.4920893609523773
epoch 26: {'accuracy': 0.914881933003844} , current_best_acc: 0.9152480322167308 train_loss: 0.12948131561279297
epoch 27: {'accuracy': 0.9165293794618341} , current_best_acc: 0.9165293794618341 train_loss: 0.030909324064850807
epoch 28: {'accuracy': 0.9097565440234303} , current_best_acc: 0.9165293794618341 train_loss: 0.41369155049324036
epoch 29: {'accuracy': 0.9145158337909574} , current_best_acc: 0.9165293794618341 train_loss: 0.10978622734546661
epoch 30: {'accuracy': 0.9088412959912137} , current_best_acc: 0.9165293794618341 train_loss: 0.1006155014038086
epoch 31: {'accuracy': 0.9130514369394106} , current_best_acc: 0.9165293794618341 train_loss: 0.037138767540454865
epoch 32: {'accuracy': 0.9172615778876075} , current_best_acc: 0.9172615778876075 train_loss: 0.7113503813743591
epoch 33: {'accuracy': 0.9141497345780707} , current_best_acc: 0.9172615778876075 train_loss: 0.11600372940301895
epoch 34: {'accuracy': 0.9168954786747209} , current_best_acc: 0.9172615778876075 train_loss: 0.506722629070282
epoch 35: {'accuracy': 0.9136005857587406} , current_best_acc: 0.9172615778876075 train_loss: 0.06643570959568024
epoch 36: {'accuracy': 0.9165293794618341} , current_best_acc: 0.9172615778876075 train_loss: 0.29717448353767395
epoch 37: {'accuracy': 0.9189090243455976} , current_best_acc: 0.9189090243455976 train_loss: 0.15061554312705994
epoch 38: {'accuracy': 0.9198751235584844} , current_best_acc: 0.9198751235584844 train_loss: 0.3212592899799347
epoch 39: {'accuracy': 0.9181768259198243} , current_best_acc: 0.9198751235584844 train_loss: 0.2020525187253952
